Analisis Sentimen Berdasarkan Komentar Publik Terhadap Toko Online Pada Media Sosial Facebook (Studi Kasus: Zalora dan BerryBenka)
Abstract
Maraknya penggunaan jejaring sosial seperti Facebook mendorong munculnya data tekstual yang tidak terbatas, sehingga muncul kebutuhan penyajian informasi tanpa mengurangi nilai dari informasi tersebut. Salah satu pemanfaatan data ini adalah untuk mengetahui opini atau sentimen publik terhadap pelayanan dan produk suatu toko online. Metodologi yang digunakan untuk melakukan analisis sentimen dimulai dari data collecting, preprocessing, feature selection, klasifikasi dan pengukuran akurasi. Metode klasifikasi Naive Bayes, k-NN dan Decision Tree digunakan untuk membandingkan hasil prediksi klasifikasi yang terbaik. Hasil analisis pengujian menunjukkan Naive Bayes memiliki kestabilan akurasi setelah diuji dengan beberapa nilai Frequent Itemset. Naive bayes memiliki rata-rata akurasi 90.3%.Kata kunci: Opini, Sentimen, Preprocessing, Feature Selection, Klasifikasi, Naïve Bayes, k-NN, Decision Tree, Frequent Itemset, AkurasiReferences
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